Cohort analysis
With cohort analysis, you can divide generated data into relevant user groups. This makes it easier to recognize valuable information and patterns across groups of users, saving a lot of time compared to looking at each individual user.
To perform a cohort analysis, you must first determine which group (cohort) you will be looking at. This group depends on the specific service, Web site or application to be analyzed. Often the people in a cohort share one or more common characteristics over a period of time.
A cohort can consist of people who visited the website during the month of March. Or a cohort consists of people of the same age or gender. So there are all sorts of characteristics that can fall under a cohort. As long as the distinguishing characteristic provides valuable data for the cohort analysis, you're fine.
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Cohort analysis is primarily used for mobile app and Web analytics, where the most popular cohorts are at the "join date. This refers to the date the user signs up, downloads the app or makes the first purchase. Looking at the trends in behavior and spending by age will give you more insight by cohort. Based on these trends, quality for new users can be better developed. Some benefits of cohort analysis include:
- Gain clear insight into the amount of revenue generated from newer and older customers by grouping into cohorts
- Be able to visualize whether the customer comes back and how often they come back. Is this after a year, six months or after just one month?
- Be able to make comparisons between social, psychological and demographic cohorts based on data. This data can then be translated into specific marketing strategies for each cohort to increase ROI
Nowadays, it is extremely easy to see online data about your users. Helpful applications such as Google Analytics help with reading different types of data. It is important to know how to measure this data with the platform you are using. By knowing this, a cohort analysis can be done properly.
